Method of providing rate tiers in wireless communication systems

ABSTRACT

The present invention provides a method of providing rate tiers in a wireless communication system. Embodiments of the method include forming, at a network element in the wireless communication system, a statistical representation of resource usage for a user in the wireless communication system as a function of location and/or time using measurements of the user&#39;s resource usage at a plurality of locations. Embodiments of the method also include defining, at the network element, a plurality of rate tiers based on the statistical representation. Each rate tier indicates a rate for a different level of resource usage offered to the user.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent Application61/411,299, filed on Nov. 8, 2010.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to communication systems, and, moreparticularly, to wireless communication systems

2. Description of the Related Art

Service providers typically provide numerous voice and/or data servicesto subscribers using one or more wired and/or wireless communicationsystems. Exemplary services include cellular telephony, access to theInternet, gaming, broadcasting or multicasting of audio and/or video,teleconferencing, multimedia programming, and the like. Mobilesubscriber units such as cell phones, personal data assistants, smartphones, pagers, text messaging devices, global positioning system (GPS)devices, network interface cards, notebook computers, and desktopcomputers may access the services provided by the communication systemsover an air interface with one or more base stations. Communicationbetween mobile units and base stations are governed by various standardsand/or protocols, such as the standards and protocols defined by the3^(rd) Generation Partnership Project (3GPP, 3GPP2).

Users can negotiate subscriptions and/or service plans with the serviceproviders. A typical service plan is separated into different levels ortiers. For example, a user can subscribe to a basic level that allows auser access to a basic level of bandwidth, a certain amount of data,and/or a particular quality-of-service (or best effort service) for theservices provided by the wireless communication system. Each user pays abasic flat rate monthly fee for the basic level of service. Users thatexpect to use more than the basic level of bandwidth or data, or requirea higher quality-of-service, may subscribe to higher level plans. Forexample, a user that plans to spend a significant amount of time playingonline games or using videoconferencing services may subscribe to a goldservice plan that provides a higher level of bandwidth, data, and/orquality-of-service than the basic level. Users pay a higher premiumprice to subscribe to the higher level service plans.

The capacity of the wireless communication system can vary significantlyover time and at different locations. Service providers therefore havedifficulty predicting the actual bandwidth, throughput, and/orquality-of-service available to subscribers to the different tiers.Consequently, users' expectations are not always met by the currentmulti-tier service plans. For example, a user that pays a premium tosubscribe to a gold service plan may expect seamless and uninterruptedservice even when using services (such as gaming and videoteleconferencing) that require significant resources such as bandwidth.Premium users may therefore be frustrated by interruptions and/ordegraded quality when the user attempts to use resource-intensiveapplications at times or in locations where the required resources arescarce, e.g., due to low capacity of the system and/or high usage byother subscribers. These frustrated users may feel that they are notgetting good value and may consider dropping the gold service plan andperhaps even switching service providers.

Service providers also have difficulty predicting resource usage of thedifferent subscribers, at least in part because of the wide variety ofservices available to each subscriber and the idiosyncratic choices madeby each subscriber. For example, one subscriber to a gold service planmay use a mobile phone exclusively for voice communication and maytherefore use significantly fewer resources than another gold serviceplan subscriber that uses a smart phone for online gaming.

The inability of service providers to predict individual resource usagecan reduce the actual capacity of the wireless communication system. Forexample, a conventional admission control algorithm assumes that eachuser requesting access to the system will utilize a predetermined amountof system resources, which may be referred to as a resource margin. Theadmission control algorithm will admit the requested call if the systemcan provide the assumed resource margin and will reject the requestedcall if it determines that it does not have sufficient resources tosupport the requested call. However, the estimated margin can be veryinaccurate when the actual resource consumption of a particular userdiffers from the expected average resource usage. Admission controlalgorithms typically assume a relatively high (or worst-case) resourcemargin and so they tend to overestimate the resources required tosupport requested calls. Consequently, system capacity may beerroneously reduced, e.g., because calls that have relatively lowresource consumption may be rejected because the resource margin forthese calls has been overestimated.

SUMMARY OF EMBODIMENTS OF THE INVENTION

The disclosed subject matter is directed to addressing the effects ofone or more of the problems set forth above. The following presents asimplified summary of the disclosed subject matter in order to provide abasic understanding of some aspects of the disclosed subject matter.This summary is not an exhaustive overview of the disclosed subjectmatter. It is not intended to identify key or critical elements of thedisclosed subject matter or to delineate the scope of the disclosedsubject matter. Its sole purpose is to present some concepts in asimplified form as a prelude to the more detailed description that isdiscussed later.

In one embodiment, a method is provided for determining rate tiers in awireless communication system. Embodiments of the method includeforming, at a network element in the wireless communication system, astatistical representation of resource usage for a user in the wirelesscommunication system as a function of location and/or time usingmeasurements of the user's resource usage at a plurality of locations.Embodiments of the method also include defining, at the network element,a plurality of rate tiers based on the statistical representation. Eachrate tier indicates a rate for a different level of resource usageoffered to the user.

In another embodiment, a method is provided for determining rate tiersin a wireless communication system. Embodiments of the method includereceiving, at a network element in the wireless communication system, arequest to admit a call from a user at a location. Embodiments of themethod also include determining, at the network element, whether toadmit the call using an estimate of a resource margin for the user atthe location. The estimate is determined based on a statisticalrepresentation of resource usage for the user as a function of location.The statistical representation is determined using measurements of theuser's resource usage at a plurality of locations.

In yet another embodiment, a method is provided for supporting ratetiers in a wireless indication system. Embodiments of the method includeforming, at a network element in the wireless communication system, astatistical representation of resource usage for a plurality of users asa function of location and/or time by combining a plurality ofindividual statistical representations of resource usage for each user.Each individual statistical representation is determined usingmeasurements of each user's resource usage at a plurality of locations.Embodiments of the method also include determining whether to modifyresource capacity of the wireless communication system by comparing thestatistical representation to a geographical distribution of resourcecapacity of the wireless communication system.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosed subject matter may be understood by reference to thefollowing description taken in conjunction with the accompanyingdrawings, in which like reference numerals identify like elements, andin which:

FIG. 1 conceptually illustrates a first exemplary embodiment of awireless communication system;

FIG. 2 conceptually illustrates a second exemplary embodiment of awireless communication system;

FIG. 3 conceptually illustrates one exemplary embodiment of a trackingdatabase that may be implemented in the embodiments of the wirelesscommunication system shown in FIGS. 1 and 2;

FIGS. 4A and 4B conceptually illustrate a third exemplary embodiment ofa wireless communication system;

FIG. 5 conceptually illustrates a comparison of resource margins usedfor call admissions in a conventional system and in embodiments of thewireless communication systems described herein; and

FIG. 6 conceptually illustrates distributions of resource usage andsystem capacity for one exemplary embodiment of a wireless communicationsystem.

While the disclosed subject matter is susceptible to variousmodifications and alternative forms, specific embodiments thereof havebeen shown by way of example in the drawings and are herein described indetail. It should be understood, however, that the description herein ofspecific embodiments is not intended to limit the disclosed subjectmatter to the particular forms disclosed, but on the contrary, theintention is to cover all modifications, equivalents, and alternativesfalling within the scope of the appended claims.

DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

Illustrative embodiments are described below. In the interest ofclarity, not all features of an actual implementation are described inthis specification. It will of course be appreciated that in thedevelopment of any such actual embodiment, numerousimplementation-specific decisions should be made to achieve thedevelopers' specific goals, such as compliance with system-related andbusiness-related constraints, which will vary from one implementation toanother. Moreover, it will be appreciated that such a development effortmight be complex and time-consuming, but would nevertheless be a routineundertaking for those of ordinary skill in the art having the benefit ofthis disclosure.

The disclosed subject matter will now be described with reference to theattached figures. Various structures, systems and devices areschematically depicted in the drawings for purposes of explanation onlyand so as to not obscure the present invention with details that arewell known to those skilled in the art. Nevertheless, the attacheddrawings are included to describe and explain illustrative examples ofthe disclosed subject matter. The words and phrases used herein shouldbe understood and interpreted to have a meaning consistent with theunderstanding of those words and phrases by those skilled in therelevant art. No special definition of a term or phrase, i.e., adefinition that is different from the ordinary and customary meaning asunderstood by those skilled in the art, is intended to be implied byconsistent usage of the term or phrase herein. To the extent that a termor phrase is intended to have a special meaning, i.e., a meaning otherthan that understood by skilled artisans, such a special definition willbe expressly set forth in the specification in a definitional mannerthat directly and unequivocally provides the special definition for theterm or phrase.

Generally, the present application describes embodiments of techniquesfor providing rate tiers for users or subscribers to services providedby a wireless communication system. Conventional service rate plansoffer every user a simple menu (e.g., gold, silver, and basic plans) andeach user selects from among the plans on offer. Higher-level plans aretypically more expensive and promise higher bandwidth, throughput,and/or quality-of-service. However, as discussed herein, the actualbandwidth, throughput, and/or quality-of-service received by individualusers can vary dramatically based upon factors such as the user'slocation, time of day, mix of wireless services, and the like. Someusers may therefore feel that they are paying a premium price for a lessthan premium service, while the level of resources available to otherusers may far exceed their needs. Still other users could dramaticallyimprove the performance of their requested services at a relativelysmall cost due to the availability of wireless resources in regionsfrequented by the user.

Embodiments of the techniques described in the present application mayaddress these drawbacks in the conventional practice by providingmechanisms that allow service plans to be tailored to each user'sgeographic and/or temporal wireless resource usage patterns. In oneexemplary embodiment, statistical representations of resource usage canbe created for each user as a function of location using measurements ofthe user's resource usage at various locations within the coverage areaof the wireless indication system. Billing rate tiers can then bedefined for the users based on the statistical representation so thateach rate tier offers a rate for a different level of resource usage. Inanother embodiment, call admission functions in the wirelesscommunication system may determine whether to admit the requested callusing an estimate of a resource margin for the user at their currentlocation. The estimate is made based on the statistical representationof resource usage for the user. Service providers may also use thestatistical representations for groups of users to determine whether tomodify resource capacity of the wireless communication system bycomparing the statistical representations to a geographical distributionof resource capacity of the wireless communication system.

FIG. 1 conceptually illustrates a first exemplary embodiment of awireless communication system 100. In the illustrated embodiment, thewireless communication system 100 includes one or more base stations 101that are part of a radio access network (RAN) 102 configured to providewireless connectivity to one or more mobile units 103 over an airinterface 104. Techniques for providing wireless connectivity are knownin the art and in the interest of clarity only those aspects of thesetechniques that are relevant to the claimed subject matter will bediscussed herein. The radio access network 102 is communicativelycoupled to a mobility management entity (MME) 105, which is a controlnode for the radio access network 102 and may be configured to performtasks such as user idle mode tracking and paging procedures, beareractivation/deactivation process, authenticating the user, and the like.The radio access network 102 is also communicatively and/orelectronically coupled to a serving gateway 110 that performs tasks suchas routing and forwarding user data packets, acting as the mobilityanchor for the user, and the like. The serving gateway 110 iscommunicatively and/or electronically coupled to a packet data networkgateway (PGW) 115, which provides connectivity from the mobile unit 103to one or more external packet data networks (PDN) 120.

The illustrated embodiment of the wireless communication system 100 alsoincludes a home subscriber server (HSS) 125, which is a master userdatabase that supports IMS network entities that handle calls. Forexample, the home subscriber server 125 may contain subscription-relatedinformation (subscriber profiles), perform authentication andauthorization of the user, and/or provide information about thesubscriber's location and IP information. The home subscriber server 125is communicatively coupled to the mobility management entity 105 and apolicy and charging rules function (PCRF) 130, which may be responsiblefor managing bandwidth, charging rates, and/or quotas within thewireless communication system 100. The PCRF 130 is communicativelyand/or electronically coupled to a subscriber profile repository (SPR)135, which stores subscriber profile information such as entitlements,rate plans, and the like.

The wireless communication system 100 may also include an onlinecharging system (OCS) 140 to perform functions related to onlinecharging and an off-line charging system (OFCS) 145 to perform functionsrelated to off-line charging. For example, service providers may useoffline and online billing functions to keep track of the chargesincurred by each subscriber unit for using the various services providedby the service provider. The 3GPP standards group has defined a set ofspecifications that may be used to implement online charging systems andoffline charging systems to cover charging in the various networkdomains (e.g., a circuit switching network domain, a packet switchingnetwork domain, and/or a wireless domain), IP multimedia subsystems, andemerging 3G application services. Offline charging is generally definedas a charging mechanism where charging information does not affect, inreal-time, the service rendered. In offline charging, charginginformation for network resource usage is collected concurrently withthat resource usage. Online charging is generally defined as a chargingmechanism where charging information can affect, in real-time, theservice rendered, and therefore a direct interaction of the chargingmechanism with session/service control is needed. In online charging,charging information for network resource usage is collectedconcurrently with that resource usage in the same fashion as in offlinecharging. However, authorization for the network resource usage must beobtained by the network prior to the actual resource usage to occur.

The wireless communication system 100 includes a tracking database 150that stores information correlating each user's resource usage tolocations, paths, and/or usage times for each user. As used herein, thephrase “resource usage” will be understood to refer to the amount ofresources of the wireless communication system 100 that are used by,consumed by, and/or allocated to a user to support wirelesscommunication. The resource usage for a particular user may refer tomeasures of the total amount of resources consumed by the user tosupport all services and/or applications available to the user oralternatively the resource usage may be used to indicate the resourcesconsumed to support a particular service/application or combinationthereof. Exemplary measures of the user's resource usage includebandwidth consumed by or allocated to the user, uplink and/or downlinkthroughput, numbers or volumes of transmitted bytes, data rates,channels or codes allocated to the user, and the like. In oneembodiment, the tracking database 150 (or other entity within thewireless communication system 100) can generate a statisticalrepresentation of resource usage for each user in the wirelesscommunication system 100 as a function of location using measurements ofthe user's resource usage at a plurality of locations. For example,measurements of the metrics can be averaged and a standard deviation ofthe measurements from the average value can be determined. Otherstatistical measures may also be applied to the collected metric data.

The statistical representation can then be saved in the trackingdatabase 150. Embodiments of the wireless communication system 100 mayimplement a user mobility tracking function that tracks (e.g., measuresor instructs other entities to measure) the per user metrics. The usermobility tracking function may then store the per user metrics. Thecollected metrics can be correlated to the access locations for eachconnection and each user. For example, the radio access networks 102 canbe configured to implement the user mobility tracking function.Exemplary metrics may include, but are not limited to, averageradiofrequency (RF) resource (e.g. bandwidth) usage, RF condition (e.g.as indicated by the modulation and coding scheme (MCS) and/or channelquality information (CQI)), duration under coverage, user location (e.g.cell/sector ID, longitude/latitude) when connected, and/or user datausage such as volume and throughput when connected. Since mobile units101 are in practice largely nomadic (vs. truly mobile), users on averagefollow a handful of deterministic paths in their daily routines. Bothfactors indicate that the statistical representations reflect meaningfulaveraging of the dynamic mobility tracking information collected by theuser mobility tracking function.

In one embodiment, the statistical representations can be used toestablish rate tiers. As used herein, the term “rate” will be understoodto refer to a measure of the cost charged to a user for access to thewireless communication system 100. In different embodiments, the ratemay be defined in different ways. For example, a billing rate mayindicate a dollar (or other currency) amount that is charged every monthto provide service to the user at the level specified by a service levelagreement (SLA) for the associated tier. For another example, the ratemay indicate a dollar amount that is charged to the user as a functionof the resources consumed such as a dollar (or other currency) amountper increment of bandwidth, a dollar amount per transmitted uplinkand/or downlink byte, and the like. Each rate tier indicates a rate thatis charged for a particular level of resource usage or range of resourceusages. Different rate tiers may be used to differentiate userexperience across tiers over a wide array of applications and/or topromote incentives towards higher tiers. For example, when the ratetiers indicate billing rates charged for a selected throughput or rangeof throughputs, the different tiers may be defined to satisfy thecriterion:

Prob[R _(tierA) >M*R _(SLA) _(—) _(tierB) ]>N %, 1≦M≦R _(SLA) _(—)_(tierA) /R _(SLA) _(—) _(tierB)  (1)

where tierB is one tier lower than tierA, the billing rate for tierB islower than the billing rate for tierA, R_(tierA) is the actual realizedconnection throughput for tierA users, and R_(tierB) is the actualrealized connection throughput for tierB users. In this embodiment,R_(SLA) _(—) _(tierX) is the service level agreement (SLA) data rate fortierX users and R_(SLA) _(—) _(tierB)<R_(SLA) _(—) _(tierA). Theparameters M, N can be varied according to design and/or implementationconsiderations. Enforcement of this criterion may be performed in theRAN 102 over the air interface 104 by making use of guaranteed bit rate(GBR) or GBR-like bearers with a guaranteed rate equal to targetR_(tier). In alternative embodiments, the rate tiers can be defined interms of other resources or combinations of resources, such asbandwidth, quality-of-service, and the like.

The statistical representation stored in the tracking database 150 maybe used to support call admission to the wireless communication system100. In one embodiment, the radio access network 102 uses thestatistical representations during call admission control procedures.For example, the radio access network 102 can access the statisticalrepresentation for the mobile unit 103 when it receives a request for acall from the mobile unit 103. The statistical representation can beused to estimate the resource margin required to admit the call whilethe mobile unit 130 is at its current location. For example, usermobility tracking information may provide RAN call admission withaverage RF resource usage (i.e. bandwidth) and condition (e.g. MCS, CQI,etc) of each user relevant to the access location, allowing the RAN 102to minimize admission margin necessary to enforce the user target rateand thereby increase and/or maximize system capacity.

In one embodiment, the wireless communication system 100 includes aservice-level agreement offering function 155 that can estimate theresource availability and potential range of service rates available toeach user. For example, the SLA offering function 155 can estimatesensible and achievable SLAs that can be offered to each user. Thewireless communication system 100 may then communicate this informationto the user, e.g., over the air interface 104. For example, a user whosigns up for low rate tier can be enticed to upgrade to higher tier ifuser tracking shows good properties along the user's typical paths. Itmay also be possible to offer location specific or location-based ratetier service for each user, e.g., a user may be offered high rate tierservice at work and low rate tier service at home. However, persons ofordinary skill in the art having benefit of the present disclosureshould appreciate that other embodiments may use the statisticalrepresentations to offer a variety of different location-dependentand/or time-dependent service plans including any number of rate tiersrepresent different definitions of the service levels. A verificationfunction 160 may be used to verify that the offered SLAs are actuallybeing provided (at least in an average or statistical sense) to theusers in accordance with their agreements. For example, the verificationfunction 160 may support verification of SLA by presenting all or partof user tracking data (or other information synthesized from this data)to operators and consumers.

Network planning may also be supported and/or enhanced using theinformation in the statistical representations of the users' resourceusage. In one embodiment, a network planning function 165 can becommunicatively and/or electronically coupled to the tracking database150. The network planning function 165 may generate maps ordistributions representing usage patterns for groups of users thataccess the wireless communication system. The maps or distributions canbe compared to the geographic distribution of service capacity of thewireless communication system 100 to identify regions of overcapacityand/or under capacity. The network planning function 165 may useinformation retrieved from the tracking database to facilitateidentification of regions where coverage or capacity may be improved,e.g., on a per rate-tier basis. For example, when high rate tier usersare found to be concentrated along a path or in a region where theoffered or promised target R_(tier) cannot be satisfied, serviceproviders may be informed that capacity or coverage expansion may beuseful and/or profitable.

FIG. 2 conceptually illustrates a second exemplary embodiment of awireless communication system 200. In the second exemplary embodiment,communication pathways between elements of the wireless communicationsystem 200 are shown and methods of operating the system 200 areillustrated. The user can request (at 205) access to the network, e.g.,by transmitting a call admission request or an access request. The usercan then be classified (at 210) using information stored in a subscriberprofile 215. For example, the user's subscriber profile may indicate theSLA service tier currently allocated to the user. In one embodiment, thesubscriber profile information may be retrieved from an HSS and conveyedto the RAN to use for admission control and/or tracking of the user. Astatistical representation of the user's resource usage can also beconveyed from the user tracking database 220 to a policy function 225,such as a policy charging and rules function, which also receivessubscriber profile information. The policy function 225 may use thisinformation to generate and convey policy and/or charging rules to anadmission control and resource allocation function 230, which may beimplemented in the RAN. For example, a user tracking profile containinguser's average RF resource usage, RF conditions, mobility, etc, may beretrieved from the tracking database 220 and conveyed to the RAN.

In the illustrated embodiment, the admission control and resourceallocation function 230 in the RAN performs admission control and mayadmit the call using the user's average resource usage from usertracking profile to minimize the resource margin needed to support theuser's target rate. In some cases, estimating the resource margin usingthe statistical representation of the user's resource usage may becritical for maximizing capacity to enable feasible service offers of awide variety of services to a large number of users. For example, usinga single assumed resource usage (such as a worst case usage scenario)for all users may cause the system to significantly overestimateresource consumption for requested calls and therefore reject anexcessively large number of requested calls that could in fact besupported by the system. Once the call is admitted, an enforcementfunction 235 (which may be implemented in the RAN) can enforce user'starget rate with an air interface scheduler that attempts to satisfyeach admitted user's minimum or guaranteed bit rate (GBR) and/or maximumbit rate (MBR) constraints with and/or without congestion in the core.In one embodiment, the enforcement function 235 may throttle trafficaccording to user target rates when under core congestion. Theenforcement function 235 in the RAN may also measure user connectionstatistics (e.g. average BW usage, average SINR/MCS/CQI, mobilitymetrics) and feed back this information, e.g., to the user trackingdatabase 220 via the allocation function 230.

The user tracking database 220 may also be used to determine anachievable SLA offering (at 240); which may be sent back to thesubscriber profile database 215 so that this information can be conveyedto the user when the user requests a connection. This information canalso be used to offer different tiers to connected users and/or toprovide information justifying the value of subscribing to a differenttier, e.g., by generating and transmitting a message that is transmittedto the user over the air interface. In one embodiment, users may be ableto respond to these messages with a request to upgrade to a differenttier and the system may respond by modifying the appropriate userprofiles and changing the service level for the user. Information in theuser tracking database 220 can also enable SLA verification (at 245) andfacilitate network planning/expansion (at 250).

FIG. 3 conceptually illustrates one exemplary embodiment of a trackingdatabase 300 that may be implemented in the embodiments of the wirelesscommunication system 100, 200 shown in FIGS. 1 and 2. In the illustratedembodiment, the tracking database 300 is used to store one or moreprofiles 305 for individual users that utilize services or applicationsprovided by the wireless communication system. The tracking database 300may be implemented at a single location within the system or may bedistributed over multiple locations throughout the system. The profile305 is indexed by a user identifier and includes a statisticalrepresentation of the resource usage of this user. In the illustratedembodiment, the statistical representation correlates the cellidentifier with the time of day (T) (or alternatively a range of times)that the user is typically found within the cell, an average usage ofvoice services (U_(V)) while the user is in the cell, and/or an averageusage of data services (U_(D)) while the user is in the cell. Units forthe usages are arbitrary and the numbers shown in FIG. 3 are onlyintended to illustrate how usage may possibly vary for differentservices in different cells at different times. Alternative embodimentsof the statistical representation may use different correlations betweenthe user's location and resource usage. For example, the user's locationmay be indicated by geographical coordinates (such as latitude andlongitude) and the resource usage may be a total daily resource usage atthe location and/or the resource usage rate when the user is at thatlocation. In other alternative embodiments, other correlations may becomputed between different quantities that represent the resource usageand/or the location of the user. Moreover, the usages may be associatedwith different services and/or applications so that per user per serviceusages can be calculated as a function of location and/or time.

FIG. 4A conceptually illustrates a third exemplary embodiment of awireless communication system 400. In the third exemplary embodiment, auser 405 may travel along a path 410 from a source cell 415 (such as acell that includes the user's home) to a destination cell 420 (such as acell that includes the user's workplace). The path 410 and the cellsassociated with the path 410 can be identified using statisticalanalysis of the travel patterns of the user 405 and each user 405 may beassociated with more than one path 410. The system 400 can also measuremetrics associated with the user 405 when it is connected to some or allof the cells along the path 410. For example, the system 400 can measurea statistical average of the resource usage for voice services andresource usage for data services. Other statistical measures, such asmeans, medians, modes, statistical deviations, likelihoods,probabilities, and the like may also be determined using the measuredresource usage data. For example, the likelihood or probability that aparticular call may require a particular level of resource usage can becalculated and used in conjunction with embodiments of the techniquesdescribed herein.

The user's resource usage can then be correlated with the cellidentifier as indicated in the bar graph 425. In the illustratedembodiment, overall usage is highest in the source cell 415 and thedestination cell 420. Usage for voice services (the lower box below thedashed line) and data services (the upper box above the dashed line) arealso highest within the source cell 415 and the destination cell 420.Overall usage drops in the intermediate cells along the path 410,primarily because data usage drops significantly in the intermediatecells. Resource usage for voice communication also drops in theintermediate cells, but to a lesser degree than the drop in the datausage. Margins for call admission may then be set to lower values in theintermediate cells and higher values in the source cell 415 and thedestination cell 420 to reflect the different patterns of resourceusage. The user 405 may also be offered an individually tailored serviceplan that provides enhanced data resource availability in the sourcecell 415 and the destination cell 420, while reducing data resourceavailability (and associated costs) in the intermediate cells along thepath 410.

FIG. 4B conceptually illustrates a third exemplary embodiment of awireless communication system 400. In the third exemplary embodiment, abar graph 430 is used to so the temporal resource usage of the user 405while in the source cell 415. Resource usage is divided into two hourintervals throughout the time of day. The user's resource usage can thenbe correlated with the difference time intervals throughout the day asindicated in the bar graph 430. In the illustrated embodiment, overallusage is highest in the source cell 415 in the mornings and evenings.Usage for voice services (the lower box below the dashed line) and dataservices (the upper box above the dashed line) are also highest at thesetimes of day. Overall usage drops at night and during the day, probablybecause the user is not as likely to be at home during these timeintervals or perhaps the user has access to a wired connection to theInternet and so is not as likely to use mobile services or uses a lessresource-intensive mix of services during the time intervals. Marginsfor call admission may then be set to lower values during the low usageperiods and higher values in the higher usage periods. The user 405 mayalso be offered an individually tailored service plan that providesenhanced resource availability in the mornings and evenings, whilereducing data resource availability (and associated costs) at othertimes of the day.

Rate tiers and/or billing plans may also be established based on theuser's resource usage patterns in different locations and/or atdifferent times. For example, when a user is going to be only at onelocation, e.g. during a known or predetermined time interval, astatistical representation of the temporal variations in a user'sresource usage at the location can be formed from metrics collectedwhile the user is at that location and used to represent the user'slikely temporal pattern of resource usage or consumption when in thatlocation. If the user can be at one of two or more locations, e.g. theuser could be at one of N different locations (where N≧1) during othertime intervals or at a subsequent time, a new combined statisticalrepresentation can be formed to represent the user's likely pattern ofresource usage or consumption when in these locations. In one case, thecombined statistical representation may be an average of metricscollected at the multiple locations. Alternatively, the user canestablish a separate or a decomposed statistical sub-representation forone or more location subsets. For instance, a location subset could bean area in the vicinity of a user's home and another location subsetcould be an area in the vicinity of the user's office. In that case, theuser may have different profiles stored in the tracking database (onefor each location subset) and the appropriate profile can be selectedand/or accessed based on estimating the user's location, e.g.,geographical coordinates provided by a GPS system associated with theuser. Different service levels and different billing rate tiers cantherefore be provided in each of the location subsets.

In one embodiment, the total cost or the effective billing rate for abilling cycle may be determined based on the relative time and/orresource usage in each location subset and/or over each time intervalassociated with each profile. For example, the user's time occupancy ineach location subset can be used to form a time weighted average(weights adding to one) of the rate tiers corresponding to each servicelevel and the time-weighted average can be used to calculate the user'sbill for the billing cycle. In other words, each rate tier may bediscounted based on the fractional proportion of time spent in eachlocation subset. The discount or weight calculation could also besimplified to be static (e.g., 50% discount for each profile in the twolocation profile example) or discounts may not be applied at all, e.g.,the weights may be set to unity for each profile so that the subscribereffectively appears as N independent users that are each accordedhis/her own tier and each pays the full (undiscounted) price in theirrespective tiers. The special case of N=1 is when a single combinedstatistical representation is used to represent the universe oflocations that the user can be in within the system. Other examples ofselected groups of locations are particular sets of cells or frequentlytraveled paths.

FIG. 5 conceptually illustrates a comparison of resource margins usedfor call admissions in a conventional system and in embodiments of thewireless communication systems described herein. In both cases, thesystem is processing six call admission requests and so the system needsto estimate the resource margin to provide an estimate of what resourcesmay need to be allocated to support the requested calls. Theconventional system sets the resource margins for each of the calls atthe same value, which is typically a large or worst-case scenario value.The conventional system therefore estimates the resources needed toadmit the calls at the level indicated by the boxes 500. In contrast,embodiments of the techniques described herein allow the system toestimate resource margins based upon the statistical representation ofthe actual resource usage of each individual user at the location (andpossibly time) of the current access request. The estimated resourcemargins 505 may therefore be lower or higher than the resource marginsestimated for the same users by the conventional system. However, theconventional system typically assumes a worst-case scenario and so onaverage the resource margins 505 estimated based on the actual resourceusage of the individual users may be lower than the resource margins 500used in the conventional system by an amount 510 shown in FIG. 5.Although in some embodiments or situations the resource margins 505 maybe larger than the resource margins 500, this is still advantageousbecause it is a more accurate representation of the likely resourceusage for the requested calls.

FIG. 6 conceptually illustrates distributions of resource usage 600 andsystem capacity 605 for one exemplary embodiment of a wirelesscommunication system. The distributions 600, 605 are measured inarbitrary units and are plotted as a function of distance along onedirection. However, persons of ordinary skill in the art having benefitof the present disclosure should appreciate that alternative embodimentsmay plot the distributions 600, 605 in any number of dimensionsincluding but not limited to two spatial dimensions and one temporaldimension. In the illustrated embodiment, the distribution 600 ofresource usage is generated by combining the statistical representationsof resource usage for a selected group of users that have been (or arecurrently) connected to the wireless communication system. For example,individual user information in the profiles stored in a trackingdatabase can be merged or combined to generate the distribution 600. Thesystem capacity 605 can be determined using a variety of methodsincluding theoretical predictions, empirical relations, a pre-existingmap created using drive-by testing during deployment of the system, amap created using measurements performed by users in the system, and thelike.

Comparison of the distributions 600, 605 can be used to facilitatenetwork planning. For example, although there are some variations, thenetwork capacity 605 and the usage 600 are basically comparable andapproximately correlated within the region 610. Consequently, it may notbe necessary or advisable to modify the system capacity in this regionas long as the overall resource availability and/or quality of serviceexperienced by each user is acceptable. Resource usage 600 fallssignificantly in the region 615 while the system capacity 605 declinesto a slightly lower level than in the region 610. The region 610 maytherefore be a good candidate for operator cost savings by reducingsystem capacity to correspond approximately to the resource usage 605 inthe region 610. Resource usage 600 rises dramatically in the region 620while the system capacity 605 continues to decline. The region 620 maytherefore be a good candidate for increasing system capacity 605, e.g.,by deploying more base stations and/or increasing the capacity of theexisting base stations.

Portions of the disclosed subject matter and corresponding detaileddescription are presented in terms of software, or algorithms andsymbolic representations of operations on data bits within a computermemory. These descriptions and representations are the ones by whichthose of ordinary skill in the art effectively convey the substance oftheir work to others of ordinary skill in the art. An algorithm, as theterm is used here, and as it is used generally, is conceived to be aself-consistent sequence of steps leading to a desired result. The stepsare those requiring physical manipulations of physical quantities.Usually, though not necessarily, these quantities take the form ofoptical, electrical, or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, principally for reasons of common usage, torefer to these signals as bits, values, elements, symbols, characters,terms, numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise, or as is apparent from the discussion,terms such as “processing” or “computing” or “calculating” or“determining” or “displaying” or the like, refer to the action andprocesses of a computer system, or similar electronic computing device,that manipulates and transforms data represented as physical, electronicquantities within the computer system's registers and memories intoother data similarly represented as physical quantities within thecomputer system memories or registers or other such information storage,transmission or display devices.

Note also that the software implemented aspects of the disclosed subjectmatter are typically encoded on some form of program storage medium orimplemented over some type of transmission medium. The program storagemedium may be magnetic (e.g., a floppy disk or a hard drive) or optical(e.g., a compact disk read only memory, or “CD ROM”), and may be readonly or random access. Similarly, the transmission medium may be twistedwire pairs, coaxial cable, optical fiber, or some other suitabletransmission medium known to the art. The disclosed subject matter isnot limited by these aspects of any given implementation.

The particular embodiments disclosed above are illustrative only, as thedisclosed subject matter may be modified and practiced in different butequivalent manners apparent to those skilled in the art having thebenefit of the teachings herein. Furthermore, no limitations areintended to the details of construction or design herein shown, otherthan as described in the claims below. It is therefore evident that theparticular embodiments disclosed above may be altered or modified andall such variations are considered within the scope of the disclosedsubject matter. Accordingly, the protection sought herein is as setforth in the claims below.

1. A method for implementation in a wireless communication system,comprising: forming, at a network element in the wireless communicationsystem, a statistical representation of resource usage for a user in thewireless communication system as a function of at least one of locationor time using measurements of the user's resource usage at a pluralityof locations; and defining, at the network element, a plurality of ratetiers based on a decomposition of the statistical representation into atleast one sub-representation corresponding to a portion of the pluralityof locations, each rate tier indicating a different billing rate for adifferent level of resource usage offered to the user in each of said atleast one location subset.
 2. The method of claim 1, comprisingmeasuring the user's resource usage at the plurality of locations duringa plurality of time intervals and conveying information indicative ofthe measurements to the network element.
 3. The method of claim 2,wherein measuring the user's resource usage comprises measuring at leastone of the user's bandwidth when connected at each location, the user'schannel condition when connected at each location, a cell or sectoridentifier of each location, coordinates of the user when connected ateach location, or the user's data volume or throughput when connected ateach location.
 4. The method of claim 1, wherein forming the statisticalrepresentation of resource usage for the user comprises forming anaverage of the measurements of the user's resource usage at eachlocation over a time interval and storing the averages in a databasethat is indexed by a user identifier and the corresponding location. 5.The method of claim 1, wherein forming the statistical representation ofresource usage for the user comprises forming a statisticalrepresentation of resource usage for the user as a function of at leastone of location or time and decomposing the statistical representationinto a plurality of sub-representations corresponding to a plurality oflocation subsets and time intervals.
 6. The method of claim 1, whereindefining the plurality of rate tiers comprises defining the plurality ofrate tiers for the user by comparing the statistical representation ofat least one of the user's bandwidth, throughput, data volume, orquality-of service to a geographic distribution of resource capacity. 7.The method of claim 6, wherein defining the plurality of rate tierscomprises defining a plurality of rate tiers in which at least one ofthe rate or the level of resource usage for each rate tier varies as afunction of at least one of time or location.
 8. The method of claim 7,comprising determining a net billing rate for the user for a billingcycle based on a weighted average of the plurality of rate tiers oversaid at least one location or time.
 9. The method of claim 8, comprisingforming the weighted average based on an arbitrary set of weightsassigned to each of the plurality of rate tiers.
 10. The method of claim8, comprising forming the weighted average based on a time weightedaverage of the plurality of rate tiers, the weights representing eithera relative or an absolute fraction of time the user is associated with acorresponding location subset.
 11. The method of claim 8 comprisingforming the weighted average based on a plurality of weights, whereineach rate is equal to the inverse of a number of location subsets. 12.The method of claim 8, comprising forming the weighted average based ona plurality of weights that are each set equal to unity.
 13. The methodof claim 1, comprising receiving an admission request for a callassociated with the user and estimating a resource margin for the callusing the statistical representation of the user's resource usage. 14.The method of claim 13, comprising determining whether to admit the callusing the estimated resource margin for the call.
 15. The method ofclaim 1, comprising combining the statistical representation of theuser's resource usage with statistical representations of other users'resource usage to form a map of resource usage as a function oflocation.
 16. The method of claim 15, comprising determining whether tomodify resource capacity by comparing the map of resource usage to ageographic distribution of resource capacity.
 17. A method forimplementation in a wireless communication system, comprising:receiving, at a network element in the wireless communication system, arequest to admit a call from a user at a location, determining, at thenetwork element, whether to admit the call using an estimate of aresource margin for the user at the location, wherein the estimate isdetermined based on a statistical representation of resource usage forthe user as a function of at least one of location or time, thestatistical representation being determined using measurements of theuser's resource usage at a plurality of locations.
 18. The method ofclaim 17, wherein determining whether to admit the call comprisescomparing the estimate of the resource margin for the user at thelocation to a geographic distribution of resource capacity of thewireless communication system.
 19. The method of claim 18, whereindetermining whether to admit the call comprises admitting the call whenthe current resource usage plus the estimate of the resource margin forthe user at the location is less than the resource capacity at said atleast one location or time.
 20. The method of claim 19, comprisingmeasuring the user's resource usage for the admitted call at one or morelocations and modifying the statistical representation of resource usagefor the user based on the measurements.
 21. The method of claim 20,wherein measuring the user's resource usage comprises measuring at leastone of the user's bandwidth when connected at each location, the user'schannel condition when connected at each location, a cell or sectoridentifier of each location, coordinates of the user when connected ateach location, or the user's data volume or throughput when connected ateach location.
 22. The method of claim 20, comprising modifying at leastone of the rate tiers based on the modified statistical representationand conveying information indicating said at least one modified ratetier to the user.
 23. The method of claim 22, comprising changing therate tier of the user when the user requests a different rate tier inresponse to receiving said information indicating said at least onemodified rate tier.
 24. The method of claim 20, comprising combining themodified statistical representation of the user's resource usage withstatistical representations of other users' resource usage to modify amap of resource usage as a function of location.
 25. The method of claim24, comprising determining whether to modify resource capacity bycomparing the modified map of resource usage to a geographicdistribution of resource capacity.
 26. A method for implementation in awireless communication system, comprising: forming, at a network elementin the wireless communication system, a statistical representation ofresource usage for a plurality of users as a function of at least one oflocation or time by combining a plurality of individual statisticalrepresentations of resource usage for each user, each individualstatistical representation being determined using measurements of eachuser's resource usage at a plurality of locations; and determiningwhether to modify resource capacity of the wireless communication systemby comparing the statistical representation to a geographicaldistribution of resource capacity of the wireless communication system.27. The method of claim 26, comprising forming the individualstatistical representations using measurements of at least one of eachuser's bandwidth when connected at each location, each user's channelcondition when connected at each location, a cell or sector identifierof each location, coordinates of each user when connected at eachlocation, or each user's data volume or throughput when connected ateach location.
 28. The method of claim 26, wherein forming theindividual statistical representations of resource usage for each usercomprises forming an average of the measurements of each user's resourceusage at each location and storing the averages in a database that isindexed by a user identifier and the corresponding location.
 29. Themethod of claim 26, wherein forming the statistical representation ofresource usage comprises forming a statistical representation ofresource usage as a function of at least one of location or time anddecomposing the statistical representation into a plurality ofsub-representations corresponding to a plurality of location subsets andtime intervals.
 30. The method of claim 26, wherein determining whetherto modify said resource capacity at a location comprises detecting atleast one of a resource capacity that is low relative to resource usageat the location or a resource capacity that is high relative to resourceusage at the location based on the comparison of the statisticalrepresentation to the geographical distribution.